Self-Tuning Neuro-PID for Stabilization of Double Inverted Pendulum

Yoshiyuki Kishida; Sigeru Omatu; Michifumi Yoshioka

doi:10.20965/jrm.1998.p0439

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JRM Vol.10 No.5 pp. 439-444

doi: 10.20965/jrm.1998.p0439

(1998)

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Self-Tuning Neuro-PID for Stabilization of Double Inverted Pendulum

Yoshiyuki Kishida, Sigeru Omatu and Michifumi Yoshioka

Department of Computer and Systems Sciences, College of Engineering, Osaka Prefecture University, Sakai, Osaka 599-8531, Japan

Received:

June 1, 1998

Accepted:

August 6, 1998

Published:

October 20, 1998

Keywords:

Neural network, PID controller, Inverted Pendulum

Abstract

This paper covers a new self-tuning neuro-PID control architecture and its application to stabilization of single and double inverted pendulums. Single-Input multioutput controls the inverted pendulum using the PID controller. PID gains are tuned using two types of neural networks. Simulation results demonstrate the effectiveness of the proposed approach.

Cite this article as:

Yoshiyuki Kishida, Sigeru Omatu, and Michifumi Yoshioka, “Self-Tuning Neuro-PID for Stabilization of Double Inverted Pendulum,” J. Robot. Mechatron., Vol.10, No.5, pp. 439-444, 1998.

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